Deciphering the Role of Vadose Zone Processes in Delayed Groundwater Nitrate Reductions
Notice bibliographique
Résumé
Beneficial Management Practices (BMPs) are designed to reduce nitrate leaching from agricultural fields and protect groundwater quality. However, temporal groundwater monitoring results from wells beneath or downgradient agricultural fields often fail to show evidence for nitrate reduction even years after BMP implementation, and the mechanisms underlying this delayed response remain poorly understood. This study conducted high-resolution characterization and monitoring to investigate nitrate transport from soil to groundwater in a 7-hectare potato rotation field in Prince Edward Island, Canada. The site features fine sandy loam soil underlain by 7–9 m of glacial till, which overlies a regional fractured “red-bed” sandstone aquifer. The water table fluctuates seasonally between 2 and 6 m below ground surface (bgs). Multi-depth groundwater monitoring was conducted over 5 years from 2011 to 2016. Historically, the field was uniformly managed under a grain-forage-potato rotation. For this study, it was divided into four management zones (A–D). Zone D was removed from crop production to eliminate agricultural nitrogen inputs, while Zones A–C continued the crop rotation. This ensured that results from Zone D were not influenced by active cropping. Additionally, the up-gradient areas of Zones C and D were forested, minimizing lateral nitrate input from outside the study area. Multilevel wells were installed along a transect in Zone D to measure nitrate concentrations at various aquifer depths bi-weekly, while water levels were monitored daily using transducers. Rock core collection with detailed core sub-sampling for nitrate distribution was conducted in 2012 to track legacy nitrate in the subsurface. Soil sampling was conducted in each zone during spring and fall. Daily tile drainage samples for nitrate analysis were collected in Zone B using an ISCO sampler. Initial soil and tile drainage sampling detected exceptionally high residual nitrate levels following the 2011 potato harvest. Using this nitrate pulse as a marker, rock coring identified it at ~3 m bgs in December 2012, while piezometer sampling detected it at the water table in spring 2014. Despite seasonal recharge, these results indicate that nitrate required approximately 2.5 years to travel through the 6-m-thick vadose zone to the aquifer. Seasonal recharge processes pushed older nitrate stored in the vadose zone downward via hydraulic pressure, creating a piston-like movement. This caused a rapid water table response but a delayed nitrate concentration response in the aquifer, highlighting that uniform rather than preferential flow dominated nitrate transport through the glacial till vadose zone. By 2016, the nitrate plume in Zone D had disappeared. The short presence of a nitrate plume in the groundwater zone suggested that aquifer matrix diffusion had a minor influence on nitrate transport at this site. Instead, the delayed response of groundwater nitrate levels to surface remediation was attributed to processes occurring in the vadose zone. This study underscores the critical role of vadose zone dynamics in governing the time lag between implementing BMPs and observing groundwater quality improvements. High-resolution monitoring of soil, drainage, and aquifer systems is essential for understanding these processes and accurately predicting the outcomes of agricultural nitrate mitigation efforts.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».